NICU-Care Dataset

NICU-Care is a high-quality video dataset designed to support visual recognition tasks in Neonatal Intensive Care Unit (NICU) scenarios, including nursing action recognition, object detection, and semantic segmentation. It was constructed in a standardized simulated NICU environment, capturing multi-view RGB videos of professional nurses performing six types of routine caregiving procedures on simulated infants. The dataset provides fine-grained temporal annotations and pixel-level segmentation masks for key objects like nurse hands, medical tools, and infant body parts. It replicates real-world clinical workflows and adopts a structured annotation system to support diverse research objectives. The dataset's design, annotation methodology, and task adaptability were rigorously validated using mainstream deep learning models. A unified data format and storage scheme ensure structured management and reusability. The public release of NICU-Care is expected to facilitate automated nursing assessment, intelligent monitoring, and data-driven training, with future extensions planned to incorporate richer annotations and multimodal sensory information to further increase its scientific and practical value.

NICU-Care是一款高质量视频数据集，专为支持新生儿重症监护病房（Neonatal Intensive Care Unit，NICU）场景下的视觉识别任务打造，涵盖护理动作识别、目标检测与语义分割三大研究方向。该数据集搭建于标准化模拟NICU环境中，采集了专业护士对模拟婴儿开展六种常规护理操作的多视角RGB视频数据。数据集为护士手部、医疗工具、婴儿身体部位等关键目标提供了细粒度时序标注与像素级分割掩码。其还原了真实临床工作流程，并采用结构化标注体系以适配多样化的研究目标。数据集的设计方案、标注方法与任务适配性均通过主流深度学习模型完成了严格的有效性验证。统一的数据格式与存储方案保障了数据集的结构化管理与可复用性。NICU-Care的公开发布有望助力自动化护理评估、智能监测与数据驱动训练的发展，研发团队还计划未来对数据集进行扩展，纳入更丰富的标注内容与多模态感知信息，以进一步提升其科学价值与实用价值。

搜集汇总

背景与挑战

背景概述

NICU-Care Dataset是一个专注于新生儿重症监护室（NICU）场景的高质量视频数据集，旨在支持护理动作识别、物体检测和语义分割等视觉识别任务。数据集包含六种常规护理程序的多视角RGB视频，并提供了精细的时间注释和像素级分割掩码，适用于深度学习模型的训练和验证。